DETAILED ACTION
This action is in response to the claims filed December 4, 2025. Claims 1-20 are pending. Claims 1, 14, and 20 are independent claims. Claims 1, 2, 14, 15, and 20 have been amended.
The objections to the drawings are withdrawn in view of Applicant’s amendments to the drawings and the specification.
The claim objections are withdrawn in view of Applicant’s amendment to claim 20.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-4, 7, 10, 13-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over “Learning-to-Rank vs Learning-to-Learn: Strategies for Regression Testing in Continuous Integration” by Bertolino et. al (hereinafter “Bertolino”), in view of CN 114564391 A (hereinafter “Huang”), further in view of US 20220179777 A1 (hereinafter “Bhat”), further in view of “test && commit || revert” by Kent Beck (hereinafter “Beck”).
Regarding claim 1, Bertolino discloses:
A system for maintaining a software application, comprising:
…
- receiving an indication of a commit operation executed on the software application to generate a build of the software application (Page 1, “An ideal TS&P technique for CI should be able to quickly identify a relevant subset of test cases that can safely and timely detect any potential regression introduced by the latest committed changes”) [Examiner’s Remarks: A commit operation (latest committed changes) is received and a subset of test cases is generated for it in response.];
…
- executing a test selection computerized model, the executing of the test selection computerized model being based at least in part on the commit operation and the plurality of test cases, an output of the test selection computerized model comprising a preliminary ranked set of test cases selected from the plurality of test cases (Page 1, “In test prioritization, LTR can be used to rank test targets (e.g., test cases or test classes) based on a testing objective (e.g., the chance of exposing failures)”; Page 3, “Clearly, they can be combined, by selecting a subset of tests, then prioritizing them [22], or by prioritizing the suite, then selecting tests, e.g., by a temporal threshold excluding the lowest priority ones [28]”; Page 3, “In the first CI cycle, we build the class-level dependency graph; at next commits, we consider the changed classes and update it accordingly (Step 1 in Fig. 1). By querying the graph, we obtain (Step 2) all the classes that transitively depend on the changed classes, along with the associated test classes, which are our test targets. These are then prioritized”) [Examiner’s remarks: Bertolino discloses selecting a ranked set of test cases using information regarding the commits (e.g. through the dependency graph) and the plurality of test cases, and outputting a ranked set by selecting and prioritizing the test cases, or vice versa. One of ordinary skill in the art understands that a list of test cases may be regarded either as a final list or as a preliminary list on which further refinement may be made.];
…
- executing at least a portion of the ranked set of test cases against the build of the software application (Page 5, “To investigate differences in the performance of algorithms in time-constrained scenarios, we consider the cases in which not all the selected test targets can be run at each cycle, e.g., because the inter-commit time is short compared to the tests execution time. We adopted the same constraints used in previous work[3] investigating the effect of time-constraints on regression testing, i.e., 25%, 50% and 75% of the number of selected test targets”) [Examiner’s remarks: At least some of the ranked test case are run (executed).]; and
Bertolino does not explicitly disclose:
at least one processor programmed to perform operations comprising:
…
- accessing test case data describing a plurality of test cases that may be executed to identify software errors;
…
- executing a defect prediction computerized model, the executing of the defect prediction computerized model being based at least in part on the commit operation, an output of the defect prediction computerized model indicating a likelihood that the commit operation introduced a defect into the software application;
- generating a ranked set of test cases based on the preliminary ranked set of test cases and the output of the defect prediction computerized model, the ranked set of test cases comprising less than all of the plurality of test cases;
…
- responsive to determining that the build of the software application failed at least one of the ranked set of test cases, executing a corrective action.
However, Huang discloses:
at least one processor programmed to perform operations comprising (Paragraph [0007]):
…
- executing a defect prediction computerized model, the executing of the defect prediction computerized model being based at least in part on the commit operation, an output of the defect prediction computerized model indicating a likelihood that the commit operation introduced a defect into the software application (Paragraph [0036], “In this embodiment, by obtaining the current digital indicators corresponding to the current code change information within a predetermined time period, wherein the current digital indicators are digital data of the code source file; using the current digital indicators to predict code program defects occurring within the predetermined time period, a prediction result is obtained; based on the prediction result and a predetermined correspondence, a set of regression test cases is determined, wherein the predetermined correspondence is a pre-determined correspondence between the application under test and the regression test cases, thereby achieving the purpose of selecting a portion of test cases from all test cases based on the predetermined correspondence for further regression testing of the software application, thus achieving the technical effect of reducing the workload of regression testing and improving the efficiency of regression testing, and thus solving the technical problems of large testing workload and low testing efficiency in the existing methods for determining test cases”) [Examiner’s remarks: The embodiment takes in digital indicators from the code source file (commit operation) and uses those features to predict code program defects (likelihood that the commit introduced a defect).];
- generating a ranked set of test cases based on the preliminary ranked set of test cases and the output of the defect prediction computerized model, the ranked set of test cases comprising less than all of the plurality of test cases (Paragraph [0036], “In this embodiment, by obtaining the current digital indicators corresponding to the current code change information within a predetermined time period, wherein the current digital indicators are digital data of the code source file; using the current digital indicators to predict code program defects occurring within the predetermined time period, a prediction result is obtained; based on the prediction result and a predetermined correspondence, a set of regression test cases is determined, wherein the predetermined correspondence is a pre-determined correspondence between the application under test and the regression test cases, thereby achieving the purpose of selecting a portion of test cases from all test cases based on the predetermined correspondence for further regression testing of the software application, thus achieving the technical effect of reducing the workload of regression testing and improving the efficiency of regression testing, and thus solving the technical problems of large testing workload and low testing efficiency in the existing methods for determining test cases”) [Examiner’s Remarks: The embodiment than takes the predicted code defects and uses that information to select a subset of test cases. Bertolino discloses generating a selection of ranked test cases, which may be treated as the preliminary ranked set of test cases. One of ordinary skill in the art may apply the method of selection based on predicted code defects described by Huang to the selected ranked test cases of Bertolino to achieve the desired subset of test cases based on predicted code defects.];
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Huang into the teachings of Bertolino to include “at least one processor programmed to perform operations comprising”, “executing a defect prediction computerized model, the executing of the defect prediction computerized model being based at least in part on the commit operation, an output of the defect prediction computerized model indicating a likelihood that the commit operation introduced a defect into the software application”, and “generating a ranked set of test cases based on the preliminary ranked set of test cases and the output of the defect prediction computerized model, the ranked set of test cases comprising less than all of the plurality of test cases”. As stated in Huang, “Typically, before software release, all regression test cases are selected to test the software to ensure product quality. However, the above method involves a large workload and low testing efficiency” (Paragraph [0002]). Huang’s method achieves “the purpose of selecting a portion of test cases from all test cases based on the predetermined correspondence for further regression testing of the software application, thus achieving the technical effect of reducing the workload of regression testing and improving the efficiency of regression testing, and thus solving the technical problems of large testing workload and low testing efficiency in the existing methods for determining test cases” (Paragraph [0036]). Huang deals in the analogous art of test case selection and minimizing test cases for final testing of software. Reducing the number of test cases based on a predicted likelihood that a commit will actually produce an error allows for faster testing by removing test cases which are likely to be unnecessary. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection with further selection based on predicted commit defects.
The combination of Bertolino and Huang does not explicitly disclose:
- accessing test case data describing a plurality of test cases that may be executed to identify software errors;
…
- responsive to determining that the build of the software application failed at least one of the ranked set of test cases, executing a corrective action.
However, Bhat discloses:
- accessing test case data describing a plurality of test cases that may be executed to identify software errors (Paragraph [0009], “Obtaining the test artifacts may include generating the test artifacts based on a test case execution history of executing the multiple test cases on the one or more legacy versions of the software application. The test artifacts may include data indicating a number of times each test case was executed, data indicating a priority that was assigned to each test case, data indicating a number of times that each test case passed, data indicating a number of times that each test case failed, data indicating an execution status of each test case a first time that the test case was executed, and/or data indicating a sequence number associated with each test case that failed [accessing test case data describing a plurality of test cases that may be executed to identify software errors]”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Bhat into the combined teachings of Bertolino and Huang to include “accessing test case data describing a plurality of test cases that may be executed to identify software errors”. As stated in Bhat, “Computational resources are preserved through implementation of the process 200 by not executing unwanted or redundant or unnecessary test cases” (Paragraph [0057]). By ranking and executing test cases by order of risk, bugs may be discovered sooner in the testing process, and safer tests don’t have to be run repetitively, saving time and computational resources. Using data about test cases helps by providing data about the test cases for selection. Therefore, it would be obvious to one or ordinary skill in the art to combine test case selection with retrieving information about test cases.
The combination of Bertolino, Huang, and Bhat does not explicitly disclose:
- responsive to determining that the build of the software application failed at least one of the ranked set of test cases, executing a corrective action.
However, Beck discloses:
- responsive to determining that the build of the software application failed at least one of the ranked set of test cases, executing a corrective action (Page 2, “The full command then is “test && commit || revert”. If the tests fail, then the code goes back to the state where the tests last passed [responsive to determining that the build of the software application failed at least one of the ranked set of test cases, executing a corrective action]”) [Examiner’s remarks: Upon a failure of the tests, a corrective action is taken (reverting to an older commit state). ].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Beck into the combined teachings of Bertolino, Huang, and Bhat to include “responsive to determining that the build of the software application failed at least one of the ranked set of test cases, executing a corrective action”. As stated in Beck, “Limbo scales technical collaboration by propagating tiny changes constantly…If thousands of tests are failing, then nobody knows what’s going on. The tests all have to pass before changes can propagate” (Pages 9-10). Test cases locate errors in code so that developers can fix the issue, ensuring correct code. Correcting the code or reverting to a previous working version of code ensures that there is a correct code version in production. Therefore, it would be obvious to one or ordinary skill in the art to combine test case selection with corrective action of code.
Regarding claim 2, the rejection of claim 1 is incorporated; and Bertolino discloses:
- … the preliminary ranked set of test cases (Page 1, “In test prioritization, LTR can be used to rank test targets (e.g., test cases or test classes) based on a testing objective (e.g., the chance of exposing failures)”; Page 3, “Clearly, they can be combined, by selecting a subset of tests, then prioritizing them [22], or by prioritizing the suite, then selecting tests, e.g., by a temporal threshold excluding the lowest priority ones [28]”; Page 3, “In the first CI cycle, we build the class-level dependency graph; at next commits, we consider the changed classes and update it accordingly (Step 1 in Fig. 1). By querying the graph, we obtain (Step 2) all the classes that transitively depend on the changed classes, along with the associated test classes, which are our test targets. These are then prioritized”) [Examiner’s Remarks: Bertolino discloses a set of test cases that are selected and ranked which may be treated as a preliminary set of test cases.]
Bertolino does not explicitly disclose:
- the ranked set of test cases comprising a subset of …
However, Huang discloses:
- the ranked set of test cases comprising a subset of (Paragraph [0036], “In this embodiment, by obtaining the current digital indicators corresponding to the current code change information within a predetermined time period, wherein the current digital indicators are digital data of the code source file; using the current digital indicators to predict code program defects occurring within the predetermined time period, a prediction result is obtained; based on the prediction result and a predetermined correspondence, a set of regression test cases is determined, wherein the predetermined correspondence is a pre-determined correspondence between the application under test and the regression test cases, thereby achieving the purpose of selecting a portion of test cases from all test cases based on the predetermined correspondence for further regression testing of the software application, thus achieving the technical effect of reducing the workload of regression testing and improving the efficiency of regression testing, and thus solving the technical problems of large testing workload and low testing efficiency in the existing methods for determining test cases”) [Examiner’s Remarks: Bertolino discloses generating a set of ranked test cases. Huang discloses generating a subset of test bases based on a predicted defect of program code to minimize the number of test cases. One of ordinary skill in the art may use Huang to further narrow the test case selection of Bertolino to retrieve a subset of the preliminary test cases.]…
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Huang into the teachings of Bertolino to include “the ranked set of test cases comprising a subset of”. As stated in Huang, “Typically, before software release, all regression test cases are selected to test the software to ensure product quality. However, the above method involves a large workload and low testing efficiency” (Paragraph [0002]). Huang’s method achieves “the purpose of selecting a portion of test cases from all test cases based on the predetermined correspondence for further regression testing of the software application, thus achieving the technical effect of reducing the workload of regression testing and improving the efficiency of regression testing, and thus solving the technical problems of large testing workload and low testing efficiency in the existing methods for determining test cases” (Paragraph [0036]). Huang deals in the analogous art of test case selection and minimizing test cases for final testing of software. Further reducing a set of test cases reduces the amount time spent running test cases that may not be impacted by an error in software. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection with choosing a subset of preliminary test cases.
Regarding claim 3, the rejection of claim 1 is incorporated; and Bertolino further discloses:
- the executing of the ranked set of test cases comprising executing the ranked set of test cases in an order indicated by a ranking of the ranked set of test cases (Pages 2-3, “In CI practices, testing is a time-constrained problem, typically dealt with by proper test selection and/or prioritization algorithms. The goal of the former is to select only those tests exercising the code directly or indirectly affected by changes. The latter reorders the entire test suite so that tests with higher priority are run first”) [Examiner’s remarks: Test case prioritization recorders a test suite to be run in an order with a priority (rank).].
Regarding claim 4, the rejection of claim 1 is incorporated; and Bertolino further discloses:
- an input to the test selection computerized model comprising historical feature data corresponding to a first test case of the plurality of test cases, the historical feature data comprising a past failure rate of the first test case and an execution time of the first test case (Page 3, Table 1, Last row regarding Test History, “Number of failed tests in the current commit, Number of failed tests per test class n commits before the current one (n=1 to 4), Total execution time of all the tests of the test class, Last time the test class was run” and described as being “Metrics based on the history of tests execution”) [Examiner’s remarks: The historical data includes data regarding time it took the test case to run and its failure in past runs.].
Regarding claim 7, the rejection of claim 1 is incorporated; and Bertolino further discloses:
- an input to the defect prediction computerized model comprising diffusion data describing a distribution of changes introduced by the commit operation to the build of the software application (Page 3, “In the first CI cycle, we build the class-level dependency graph;2 at next commits, we consider the changed classes and update it accordingly (Step 1 in Fig. 1). By querying the graph, we obtain (Step 2) all the classes that transitively depend on the changed classes, along with the associated test classes, which are our test targets. These are then prioritized”).
Regarding claim 10, the rejection of claim 1 is incorporated; and Bertolino does not explicitly disclose:
- an input to the defect prediction computerized model comprising history data describing previous changes to the software application.
However, Huang discloses:
- an input to the defect prediction computerized model comprising history data describing previous changes to the software application (Paragraph [0048], “Optionally, the third commit code information at the start time of the historical period and the fourth commit code information at the end time of the historical period are obtained; historical code change information is determined based on the third commit code information and the fourth commit code information; and the historical code files in the historical code change information are converted into the corresponding historical digital indicators”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Huang into the teachings of Bertolino to include “an input to the defect prediction computerized model comprising history data describing previous changes to the software application”. As stated in Huang, “Typically, before software release, all regression test cases are selected to test the software to ensure product quality. However, the above method involves a large workload and low testing efficiency” (Paragraph [0002]). Huang’s method achieves “the purpose of selecting a portion of test cases from all test cases based on the predetermined correspondence for further regression testing of the software application, thus achieving the technical effect of reducing the workload of regression testing and improving the efficiency of regression testing, and thus solving the technical problems of large testing workload and low testing efficiency in the existing methods for determining test cases” (Paragraph [0036]). Huang deals in the analogous art of test case selection and minimizing test cases for final testing of software. Using historical test data allows the model to take into account the effects of previous changes for prediction. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection with a record of previous changes.
Regarding claim 13, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, and Bhat does not explicitly disclose:
- the corrective action comprising accessing a good build of the software application generated by a good commit operation prior to the commit operation.
However, Beck discloses:
- the corrective action comprising accessing a good build of the software application generated by a good commit operation prior to the commit operation (Page 2, “The full command then is “test && commit || revert”. If the tests fail, then the code goes back to the state where the tests last passed”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Beck into the combined teachings of Bertolino, Huang, and Bhat to include “the corrective action comprising accessing a good build of the software application generated by a good commit operation prior to the commit operation”. As stated in Beck, “Limbo scales technical collaboration by propagating tiny changes constantly…If thousands of tests are failing, then nobody knows what’s going on. The tests all have to pass before changes can propagate” (Pages 9-10). Test cases locate errors in code so that developers can fix the issue, ensuring correct code. Correcting the code or reverting to a previous working version of code ensures that there is a correct code version in production. Therefore, it would be obvious to one or ordinary skill in the art to combine test case selection with corrective action of code.
Claims 14-17 are method claims corresponding to the system claims hereinabove (claims 1-4 respectively). Therefore, claims 14-17 are rejected for the same reasons as set forth in the rejections of claims 1-4 respectively.
Claim 20 is a non-transitory machine-readable medium claim corresponding to the system claims hereinabove (claim 1). Therefore, claim 20 is rejected for the same reasons as set forth in the rejections of claim 1.
Claims 5-6, 8, 11, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over “Learning-to-Rank vs Learning-to-Learn: Strategies for Regression Testing in Continuous Integration” by Bertolino et. al (hereinafter “Bertolino”), in view of CN 114564391 A (hereinafter “Huang”), further in view of US 20220179777 A1 (hereinafter “Bhat”), further in view of “test && commit || revert” by Kent Beck (hereinafter “Beck”), further in view of US 20220188215 A1 (hereinafter “Goswami”).
Regarding claim 5, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, Bhat, and Beck does not explicitly disclose:
- an input to the test selection computerized model comprising lexical feature data describing a name of a first test case of the plurality of test cases.
However, Goswami discloses:
- an input to the test selection computerized model comprising lexical feature data describing a name of a first test case of the plurality of test cases (Paragraph [0021], “A test case typically comprises an identification, a summary/description (which can be searched), steps forming part of the test, and other related metadata/contextual data associated with the test case”) [Examiner’s remarks: Test cases comprise a name (identification) which is used in test case selection when mapping].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Goswami into the combined teachings of Bertolino, Huang, Bhat, and Beck to include “an input to the test selection computerized model comprising lexical feature data describing a name of a first test case of the plurality of test cases”. As stated in Goswami, “The current subject matter is directed to enhanced techniques for testing a code base by identifying a minimal amount of test cases that need to be executed in response to an update or other change to the code base (especially as applicable to versioning updates to a continually evolving code base)” (Paragraph [0020]). Goswami deals in the analogous art of test case selection and minimizing test cases for final testing of software. Using name of test cases in the computerized model allows for identification of possible features or use of a test case. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection of with test case names.
Regarding claim 6, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, Bhat, and Beck does not explicitly disclose:
- an input to the test selection computerized model comprising coverage data describing a number of modified code elements of the build the software application are covered by a first test case of the plurality of test cases.
However, Goswami discloses:
- an input to the test selection computerized model comprising coverage data describing a number of modified code elements of the build the software application are covered by a first test case of the plurality of test cases (Paragraph [0003], “The call graph can be a directed call graph comprising a plurality of connected nodes in which a first subset of the connected nodes are method nodes representing each method in the code base in which unidirectional edges connecting method nodes correspond to invocations by a calling method to a callee method, and in which a second subset of the connected nodes are test case nodes representing each of a plurality of available test cases to test the code base. The test case nodes are each coupled to one or more method nodes by unidirectional edges that correspond to coverage of the method by the test case corresponding to the connected test case node. The call graph is traversed from each method node corresponding to the identified methods changed in the code base to identify test cases covering such methods”) [Examiner’s remarks: The edges of each test case node describe the code which it covers. The code coverage of the first test is determined for generating the graph].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Goswami into the combined teachings of Bertolino, Huang, Bhat, and Beck to include “an input to the test selection computerized model comprising coverage data describing a number of modified code elements of the build the software application are covered by a first test case of the plurality of test cases”. As stated in Goswami, “The current subject matter is directed to enhanced techniques for testing a code base by identifying a minimal amount of test cases that need to be executed in response to an update or other change to the code base (especially as applicable to versioning updates to a continually evolving code base)” (Paragraph [0020]). Goswami deals in the analogous art of test case selection and minimizing test cases for final testing of software. Using test coverage data of each test case allows for determination of the minimum number of test cases needed to cover a changed code. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection of with test coverage analysis.
Regarding claim 8, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, Bhat, and Beck does not explicitly disclose:
- an input to the defect prediction computerized model comprising size data describing a size of a change introduced by the commit operation to the build of the software application.
However, Goswami discloses:
- an input to the defect prediction computerized model comprising size data describing a size of a change introduced by the commit operation to the build of the software application (Paragraph [0024], “The anomaly handler 120 can be used to handle less frequent situations such as a code change implicating more than 30% of the test cases or a code change having a number of files above a pre-defined threshold (e.g., five or more files)”) [Examiner’s remarks: The selection model takes into account the amount of code that is changes in order to determine if different action should be taken.].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Goswami into the combined teachings of Bertolino, Huang, Bhat, and Beck to include “an input to the defect prediction computerized model comprising size data describing a size of a change introduced by the commit operation to the build of the software application”. As stated in Goswami, “The current subject matter is directed to enhanced techniques for testing a code base by identifying a minimal amount of test cases that need to be executed in response to an update or other change to the code base (especially as applicable to versioning updates to a continually evolving code base)” (Paragraph [0020]). Goswami deals in the analogous art of test case selection and minimizing test cases for final testing of software. Knowledge of the amount of code that is changed allows for impact analysis and a determination of whether analysis should be run. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection with the amount of code changed as a feature.
Regarding claim 11, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, Bhat, and Beck does not explicitly disclose:
- an input to the defect prediction computerized model comprising indentation data describing a number of indentations introduced to the software application by the commit operation.
However, Goswami discloses:
- an input to the defect prediction computerized model comprising indentation data describing a number of indentations introduced to the software application by the commit operation (Paragraph [0024], “Further, the anomaly handler 120 can provide that a predefined set of critical tests are executed when there are white space changes and the like.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Goswami into the combined teachings of Bertolino, Huang, Bhat, and Beck to include “an input to the defect prediction computerized model comprising indentation data describing a number of indentations introduced to the software application by the commit operation”. As stated in Goswami, “The current subject matter is directed to enhanced techniques for testing a code base by identifying a minimal amount of test cases that need to be executed in response to an update or other change to the code base (especially as applicable to versioning updates to a continually evolving code base)” (Paragraph [0020]). Goswami deals in the analogous art of test case selection and minimizing test cases for final testing of software. White space changes may indicate changes in the function structure of a code, which can be important for change analysis. Therefore, it would be obvious to one of ordinary skill in the art to combine test case selection of with indent changes.
Claims 18 and 19 are method claims corresponding to the system claims hereinabove (claims 5 and 6 respectively). Therefore, claims 18 and 19 are rejected for the same reasons as set forth in the rejection of claims 5 and 6, respectively.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over “Learning-to-Rank vs Learning-to-Learn: Strategies for Regression Testing in Continuous Integration” by Bertolino et. al (hereinafter “Bertolino”), in view of CN 114564391 A (hereinafter “Huang”), further in view of US 20220179777 A1 (hereinafter “Bhat”), further in view of “test && commit || revert” by Kent Beck (hereinafter “Beck”), further in view of US 20180260312 A1 (hereinafter “Strachan”).
Regarding claim 9, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, Bhat, and Beck does not explicitly disclose:
- an input to the defect prediction computerized model comprising purpose data describing a purpose of at least one change introduced by the commit operation to the build of the software application.
However, Strachan discloses:
- an input to the defect prediction computerized model comprising purpose data describing a purpose of at least one change introduced by the commit operation to the build of the software application (Paragraph [0011], “An example method disclosed herein includes detecting a commit of an application code based on a commit identifier in a request, the commit to update the application code; determining characteristics of the commit from a repository of commit records; and selecting tests for the commit based on the characteristics of the commit, the tests to be executed to validate the updated application code”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Strachan into the combined teachings of Bertolino, Huang, Bhat, and Beck to include “an input to the defect prediction computerized model comprising purpose data describing a purpose of at least one change introduced by the commit operation to the build of the software application”. As stated in Strachan, “In many instances of these systems, test execution is performed through annotations in the application code which limits flexibility in testing and limits the test selection to those selected by developers of the application code. ... Examples herein allow for dynamic selection of tests for an application code based on characteristics of a commit of the application code” (Paragraph [0010]). Using a purpose stated in the commit allows makes it easier to parse the purpose of a commit, and tailor test cases to that purpose. This saves time in the development pipeline. Therefore, it would be obvious to one or ordinary skill in the art to combine test case selection with input of commit purpose.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over “Learning-to-Rank vs Learning-to-Learn: Strategies for Regression Testing in Continuous Integration” by Bertolino et. al (hereinafter “Bertolino”), in view of CN 114564391 A (hereinafter “Huang”), further in view of US 20220179777 A1 (hereinafter “Bhat”), further in view of “test && commit || revert” by Kent Beck (hereinafter “Beck”), further in view of US 20180239898 A1 (hereinafter “Haerterich”).
Regarding claim 12, the rejection of claim 1 is incorporated; and the combination of Bertolino, Huang, Bhat, and Beck does not explicitly disclose:
- the corrective action comprising sending a report message to a developer user, the report message comprising an indication of the commit operation.
However, Haerterich discloses:
- the corrective action comprising sending a report message to a developer user, the report message comprising an indication of the commit operation (Abstract, “The computing device may determine a first anomalous commit of the plurality of commits and generate an alert message indicating a first code segment modified by the first commit”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Haerterich into the combined teachings of Bertolino, Huang, Bhat, and Beck to include “the corrective action comprising sending a report message to a developer user, the report message comprising an indication of the commit operation”. As stated in Haerterich, “For example, the administrative user may review the commit and subsequently allow or decline the anomalous commit” (Paragraph [0016]). Executing test cases and generating a test report is well known in the art of software testing. Generating an alert to the developer to indicate the area in which the failure occurs allows for better debugging of code. Therefore, it would be obvious to one or ordinary skill in the art to combine test case selection with providing a report for failed test cases.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/V.W.D./Examiner, Art Unit 2191 /WEI Y MUI/Supervisory Patent Examiner, Art Unit 2191
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